Nonlinear fuzzy classification models have better classification performance than linear fuzzy classifiers. In many nonlinear fuzzy classification problems, piecewise-linear fuzzy discriminant functions can approximate nonlinear fuzzy discriminant fu...
Neural networks : the official journal of the International Neural Network Society
Mar 8, 2019
Like most machine learning algorithms, Echo State Networks possess several hyperparameters that have to be carefully tuned for achieving best performance. For minimizing the error on a specific task, we present a gradient based optimization algorithm...
OBJECTIVE: Deep learning models can learn representations of data that extract useful information in order to perform prediction without feature engineering. In this paper, an electromyography (EMG) control scheme with a regression convolutional neur...
Computer methods and programs in biomedicine
Mar 8, 2019
BACKGROUND AND OBJECTIVES: In recent decades, cancer has become one of the most fatal and destructive diseases which is threatening humans life. Accordingly, different types of cancer treatment are studied with the main aim to have the best treatment...
INTRODUCTION: Using machine learning techniques, we developed a brief questionnaire to aid neurologists and neuropsychologists in the screening of mild cognitive impairment (MCI) and dementia.
IEEE journal of biomedical and health informatics
Mar 7, 2019
OBJECTIVE: The complex nature of Parkinson's disease (PD) makes difficult to rate its severity, mainly based on the visual inspection of motor impairments. Wearable sensors have been demonstrated to help overcoming such a difficulty, by providing obj...
We present machine learning models of human genome three-dimensional structure that combine one dimensional (linear) sequence specificity, epigenomic information, and transcription factor binding profiles, with the polymer-based biophysical simulatio...
Data mining methods based on machine learning play an increasingly important role in drug design and discovery. In the current work, eight machine learning methods including decision trees, k-Nearest neighbor, support vector machines, random forests,...
Prediction of biological and toxicological properties of small molecules using in silico approaches has become a wide practice in pharmaceutical research to lessen the cost and enhance productivity. The development of a tool "ChemSuite," a stand-alon...
International journal of environmental research and public health
Mar 7, 2019
Morbidity prediction can be useful in improving the effectiveness and efficiency of medical services, but accurate morbidity prediction is often difficult because of the complex relationships between diseases and their influencing factors. This study...
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